Analysis of Breast Cancer Dataset Using Big Data Algorithms for Accuracy of Diseases Prediction

Abstract

Data Mining Techniques easily handle and solve the problem of handling the massive amount of data due to heterogeneous data, missing data, inconsistent data. HealthCare is one of the most important applications of Big Data. Diagnosis of diseases like cancer at an early stage is also very crucial. This paper focuses on the prediction model analysis for the breast cancer diagnosis either benign or malignant at an early stage as it increases the chances for successful treatment So predicting breast cancer at benign increases the survival rate of women. Data mining classification algorithm like SVM, Naive Bayes, k-NN, Decision Tree compares a variety of statistical techniques like accuracy, sensitivity, specification, positive prediction value, negative predictive value, area under curve and plotted ROC curve in R analytical tool which is promising independent tool for handling huge datasets is proven better in a prediction of the breast cancer diagnosis.